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The swift and ongoing rise of global temperatures over the past decades led to an increasing number of climate variables showing statistically significant changes compared to their pre-industrial state. Determining when these climate signals emerge from the noise of internal climate variability (i.e., estimating the time of emergence, ToE) is crucial for climate risk assessments and adaptation planning. However, robustly disentangling the climate signal from internal variability represents a challenging task. While climate projections are communicated increasingly frequently through global warming levels (GWLs), the ToE is usually still expressed in terms of time horizons. Here, we present a framework to robustly derive global warming levels of emergence (GWLoE) using five single-model initial-condition large ensembles (SMILEs) and apply it to four selected temperature and precipitation indices. We show that the concept of GWLoE is particularly promising to constrain temperature projections and that it proves a viable tool to communicate scientific results. We find that > 85 % of the global population is exposed to emerged signals of nighttime temperatures at a GWL of 1.5 °C, increasing to > 95 % at 2.0 °C. Daily maximum temperature follows a similar yet less pronounced path. Emerged signals for mean and extreme precipitation start appearing at current GWLs and increase steadily with further warming (∼ 10 % population exposed at 2.0 °C). Related probability ratios for the occurrence of extremes indicate a strong increase with widespread saturation of temperature extremes (extremes relative to historical conditions occur every year) reached below 2.5 °C warming particularly in (sub)tropical regions. These results indicate that we are in a critical period for climate action as every fraction of additional warming substantially increases the adverse effects on human wellbeing. [ABSTRACT FROM AUTHOR]

Afforestation is an important mitigation strategy for climate change due to its carbon sequestration potential. Besides this favorable biogeochemical effect on global CO 2 concentrations, afforestation also affects the regional climate by changing the biogeophysical land surface characteristics. In this study, we investigate the effects of an idealized global CO 2 reduction to pre-industrial conditions by a Europe-wide afforestation experiment on the regional longwave radiation balance, starting in the year 1986 on a continent entirely covered with grassland. Results show that the impact of biogeophysical processes on the surface temperatures is much stronger than that of biogeochemical processes. Furthermore, biogeophysically induced changes of the surface temperatures, atmospheric temperatures, and moisture concentrations are as important for the regional longwave radiation balance as the global CO 2 reduction. While the outgoing longwave radiation is increased in winter, it is reduced in summer. In terms of annual total, a Europe-wide afforestation has a regional warming effect despite reduced CO 2 concentrations. Thus, even for an idealized reduction of the global CO 2 concentrations to pre-industrial levels, the European climate response to afforestation would still be dominated by its biogeophysical effects. [ABSTRACT FROM AUTHOR]

Climate warming is accelerating the changes in the global terrestrial ecosystems and particularly those in the northern high latitudes (NHLs; poleward of 50 ∘ N) and rendering the land–atmosphere carbon exchange highly uncertain. The Coupled Model Intercomparison Project Phase 6 (CMIP6) employs the most updated climate models to estimate terrestrial ecosystem carbon dynamics driven by a new set of socioeconomic and climate change pathways. By analyzing the future (2015–2100) carbon fluxes estimated by 10 CMIP6 models, we quantitatively evaluated the projected magnitudes, trends, and uncertainties in the global and NHL carbon fluxes under four scenarios plus the role of NHLs in the global terrestrial ecosystem carbon dynamics. Overall, the models suggest that the global and NHL terrestrial ecosystems will be consistent carbon sinks in the future, and the magnitude of the carbon sinks is projected to be larger under scenarios with higher radiative forcing. By the end of this century, the models on average estimate the NHL net ecosystem productivity (NEP) as 0.54 ± 0.77, 1.01 ± 0.98, 0.97 ± 1.62, and 1.05 ± 1.83 Pg C yr -1 under SSP126, SSP245, SSP370, and SSP585, respectively. The uncertainties are not substantially reduced compared with earlier results, e.g., the Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP). Although NHLs contribute a small fraction of the global carbon sink (∼ 13 %), the relative uncertainties in NHL NEP are much larger than the global level. Our results provide insights into future carbon flux evolutions under future scenarios and highlight the urgent need to constrain the large uncertainties associated with model projections for making better climate mitigation strategies. [ABSTRACT FROM AUTHOR]

Building on CMIP6 climate simulations, updated global and regional observations, and recently introduced statistical methods, we provide an updated assessment of past and future warming over France. Following the IPCC AR6 and recent global-scale studies, we combine model results with observations to constrain climate change at the regional scale. Over mainland France, the forced warming in 2020 with respect to 1900–1930 is assessed to be 1.66 [1.41 to 1.90] ∘ C, i.e., in the upper range of the CMIP6 estimates, and is almost entirely human-induced. A refined view of the seasonality of this past warming is provided through updated daily climate normals. Projected warming in response to an intermediate emission scenario is assessed to be 3.8 ∘ C (2.9 to 4.8 ∘ C) in 2100 and rises up to 6.7 [5.2 to 8.2] ∘ C in a very high emission scenario, i.e., substantially higher than in previous ensembles of global and regional simulations. Winter warming and summer warming are expected to be about 15 % lower than and 30 % higher than the annual mean warming, respectively, for all scenarios and time periods. This work highlights the importance of combining various lines of evidence, including model and observed data, to deliver the most reliable climate information. This refined regional assessment can feed adaptation planning for a range of activities and provides additional rationale for urgent climate action. Code is made available to facilitate replication over other areas or political entities. [ABSTRACT FROM AUTHOR]

Global economic production – the world gross domestic product (GDP) – has been rising steadily relative to global primary energy demands, lending hope that technological advances can drive a gradual decoupling of society from its resource needs and associated environmental pollution. Here we present a contrasting argument: in each of the 50 years following 1970 for which reliable data are available, 1 exajoule of world energy was required to sustain each 5.50±0.21 trillion year 2019 US dollars of a global wealth quantity defined as the cumulative inflation-adjusted economic production summed over all history. No similar scaling was found to apply between energy consumption and the more familiar quantities of yearly economic production, capital formation, or physical capital. Considering that the scaling has held over half a century, a period that covers two-thirds of the historical growth in world energy demands, the implication is that inertia plays a far more dominant role in guiding societal trajectories than has generally been permitted in macroeconomics models or by policies that prescribe rapid climate mitigation strategies. If so, environmental impacts will remain strongly tethered to even quite distant past economic production – an unchangeable quantity. As for the current economy, it will not in fact decouple from its resource needs. Instead, simply maintaining existing levels of world inflation-adjusted economic production will require sustaining growth of energy consumption at current rates. [ABSTRACT FROM AUTHOR]

While climate change mitigation targets necessarily concern maximum mean state changes, understanding impacts and developing adaptation strategies will be largely contingent on how climate variability responds to increasing anthropogenic perturbations. Thus far Earth system modeling efforts have primarily focused on projected mean state changes and the sensitivity of specific modes of climate variability, such as the El Niño–Southern Oscillation. However, our knowledge of forced changes in the overall spectrum of climate variability and higher-order statistics is relatively limited. Here we present a new 100-member large ensemble of climate change projections conducted with the Community Earth System Model version 2 over 1850–2100 to examine the sensitivity of internal climate fluctuations to greenhouse warming. Our unprecedented simulations reveal that changes in variability, considered broadly in terms of probability distribution, amplitude, frequency, phasing, and patterns, are ubiquitous and span a wide range of physical and ecosystem variables across many spatial and temporal scales. Greenhouse warming in the model alters variance spectra of Earth system variables that are characterized by non-Gaussian probability distributions, such as rainfall, primary production, or fire occurrence. Our modeling results have important implications for climate adaptation efforts, resource management, seasonal predictions, and assessing potential stressors for terrestrial and marine ecosystems. [ABSTRACT FROM AUTHOR]

Solar photovoltaics (PV) plays an essential role in decarbonizing the European energy system. However, climate change affects surface solar radiation and will therefore directly influence future PV power generation. We use scenarios from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) for a mitigation (SSP1-2.6) and a fossil-fuel-dependent (SSP5-8.5) pathway in order to quantify climate risk for solar PV in Europe as simulated by the Global Solar Energy Estimator (GSEE). We find that PV potential increases by around 5 % in the mitigation scenario, suggesting a positive feedback loop between climate change mitigation and PV potential. While increased clear-sky radiation and reduced cloud cover go hand in hand in SSP1-2.6, the effect of a decrease in clear-sky radiation is outweighed by a decrease in cloud cover in SSP5-8.5, resulting in an increase in all-sky radiation. Moreover, we find that the seasonal cycle of PV generation changes in most places, as generation grows more strongly in winter than in summer (SSP1-2.6) or increases in summer and declines in winter (SSP5-8.5). We further analyze climate change impacts on the spatial variability of PV power generation. Similar to the effects anticipated for wind energy, we report an increase in the spatial correlations of daily PV production with large inter-model agreement yet relatively small amplitude, implying that PV power balancing between different regions in continental Europe will become more difficult in the future. Thus, based on the most recent climate simulations, this research supports the notion that climate change will only marginally impact renewable energy potential, while changes in the spatiotemporal generation structure are to be expected and should be included in power system design. [ABSTRACT FROM AUTHOR]

Sequestration of soil organic carbon (SOC) on cropland has been proposed as a climate change mitigation strategy to reduce global greenhouse gas (GHG) concentrations in the atmosphere, which in particular is needed to achieve the targets proposed in the Paris Agreement to limit the increase in atmospheric temperature to well below 2 ∘ C. We analyze the historical evolution and future development of cropland SOC using the global process-based biophysical model LPJmL, which was recently extended by a detailed representation of tillage practices and residue management (version 5.0-tillage2). We find that model results for historical global estimates for SOC stocks are at the upper end of available literature, with ∼2650 Pg C of SOC stored globally in the year 2018, ∼170 Pg C of which is stored in cropland soils. In future projections, assuming no further changes in current cropland patterns and under four different management assumptions with two different climate forcings, RCP2.6 and RCP8.5, results suggest that agricultural SOC stocks decline in all scenarios, as the decomposition of SOC outweighs the increase in carbon inputs into the soil from altered management practices. Different climate change scenarios, as well as assumptions on tillage management, play a minor role in explaining differences in SOC stocks. The choice of tillage practice explains between 0.2 % and 1.3 % of total cropland SOC stock change in the year 2100. Future dynamics in cropland SOC are most strongly controlled by residue management: whether residues are left on the field or harvested. We find that on current cropland, global cropland SOC stocks decline until the end of the century by only 1.0 % to 1.4 % if residue retention management systems are generally applied and by 26.7 % to 27.3 % in the case of residue harvest. For different climatic regions, increases in cropland SOC can only be found for tropical dry, warm temperate moist, and warm temperate dry regions in management systems that retain residues. [ABSTRACT FROM AUTHOR]